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检索条件"主题词=Scheduling algorithms"

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scheduling jobs with stochastic holding costs 35

Scheduling jobs with stochastic holding costs

引用

35th Conference on Neural Information Processing Systems (NeurIPS)

作者： Lee, Dabeen Vojnovic, Milan Inst for Basic Sci Korea Discrete Math Grp Daejeon South Korea London Sch Econ Dept Stat London England

ISBN: (纸本)9781713845393

This paper proposes a learning and scheduling algorithm to minimize the expected cumulative holding cost incurred by jobs, where statistical parameters defining their individual holding costs are unknown a priori. In each time slot, the server can process a job while receiving the realized random holding costs of the jobs remaining in the system. Our algorithm is a learning-based variant of the c mu rule for scheduling: it starts with a preemption period of fixed length which serves as a learning phase, and after accumulating enough data about individual jobs, it switches to nonpreemptive scheduling mode. The algorithm is designed to handle instances with large or small gaps in jobs' parameters and achieves near-optimal performance guarantees. The performance of our algorithm is captured by its regret, where the benchmark is the minimum possible cost attained when the statistical parameters of jobs are fully known. We prove upper bounds on the regret of our algorithm, and we derive a regret lower bound that is almost matching the proposed upper bounds. Our numerical results demonstrate the effectiveness of our algorithm and show that our theoretical regret analysis is nearly tight.

关键词： scheduling algorithms

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An Efficient Downlink-QoS Aware scheduling Approach for Adopting Wyner-Ziv Code 17

An Efficient Downlink-QoS Aware Scheduling Approach for Adop...

引用

17th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC)

作者： Almutawa, Khaled Sultan, Radwa Refaey, Ahmed Rahman, Md Jahidur Manhattan Coll Riverdale NY 10471 USA Western Univ London ON Canada Qualcomm San Diego CA USA

ISBN: (纸本)9781728186160

The next-generation cellular networks are facing several challenges. Precisely, according to recent statistics, by 2021, video traffic will represent 82% of the IP traffic. This demand increase will affect the users' quality-of-service (QoS). Accordingly, integrating appropriate distributed source coding (DSC) frameworks for mobile data traffic is crucially needed. Wyner-Ziv coding is considered a great solution to the high demand for video traffic. However, in LTE-A, the current standard of quality-of-service class identifier (QCI) gives a higher priority to the best-effort traffic, i.e., FTP and the rate -constrained traffic, i.e., VoIP. This current prioritization may not be suitable for the growing demands for the delay-constrained traffic, i.e., video traffic. Accordingly, in this paper, we investigate the effect of giving higher priority to the video -traffic on the QoS. To address this problem, we propose a QoS-aware downlink scheduler in a single-cell LTE network. In the proposed packet scheduler, we use a utility-based scheduling approach to study the effect of adopting Wyner-Ziv coding with prioritizing video traffic over other traffic types. Numerical results confirm that when using the Wyner-Ziv coding, changing the traffic priority to grant the video traffic the highest, will not impact the system's performance compared to other existing schemes.

关键词： Wireless communication scheduling algorithms Quality of service Telecommunication traffic Jitter Video compression Throughput

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PISA architecture chip resource scheduling algorithm design and implementation

PISA architecture chip resource scheduling algorithm design ...

引用

Electrical Engineering, Big Data and algorithms (EEBDA), IEEE International Conference on

作者： Zhu Tao Anhui University Hefei China

In order to speed up the efficiency in designing PISA, a series of resource constraints are imposed. The resource scheduling situation under data dependency, control dependency, and various resource dependency constraints is to be explored. In this regard, a mixed integer programming model is developed and the optimization objective is determined to keep the number of occupied pipeline stages as short as possible. On the one hand, the data pre-processing work can be carried out, and the data can be transformed into a matrix of 0-1 variables to facilitate the control of the basic information in each module, and the processed data are judged to determine whether the decision variables can satisfy the constraints; on the other hand, the constraints limiting the objective function already in the problem are determined, and the corresponding equations are listed for the three different data dependencies of read-after-write, write-after-read, and write-after-write. At the same time to find the constraints implied by the problem itself, according to the linking relationship of the basic blocks in each board to adjust the order of the boards, due to the directed basic block linking information determines between adjacent boards, any basic block of the latter board must be linked with a certain basic block of the previous board, that is, the remaining hidden constraints can be found by the Big M method. After determining the complete decision variables, constraints and objective functions, a mixed integer programming model can be established to optimize the minimum number of occupied pipeline levels as the objective, and the results are calculated by using the lingo solver, and finally the results are optimized and verified by the heuristic algorithm - particle swarm algorithm to obtain the pipeline of problem one The number of basic blocks is the most when the number of levels is 4, and the corresponding number is 57, and the total number of pipeline levels is 53 at this ti

关键词： Integer programming Limiting scheduling algorithms Heuristic algorithms Pipelines Process control scheduling

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Energy-Efficient Routing of Information Exchanges in the Network of Autonomous Underwater Vehicles 11

Energy-Efficient Routing of Information Exchanges in the Net...

引用

11th Mediterranean Conference on Embedded Computing (MECO) / 3rd Summer School on Cyber-Physical + Systems and Internet of Things (CPS and IoT)

作者： Gruzlikov, Alexander M. Kolesov, Nikolai, V Litunenko, Elisaveta G. Tolmacheva, Marina, V State Res Ctr Russian Federat Concern CSRI Elektr JSC 30A Malaya Posadskay Ul St Petersburg Russia

ISBN: (纸本)9781665468282

The paper considers the issues of constructing an energy-efficient message routing procedure in a network of autonomous underwater vehicles. Information interaction between network agents is carried out using underwater sound communication, the feature of which is non-directional signal emission, a speed limit (kilobits per second) and a limitation of the exchange radius. The distance restriction leads to the need to form a route using underwater vehicle as message repeaters. The study focuses on the problem of ordering messages in each of the vehicle at the stage of the transmission session and reduces to a well-known problem statement (flow shop)-scheduling according to the criterion of the minimum average time spent working in the system. An algorithm for scheduling communication sessions based on the concept of a solvable class of systems is proposed. The developed algorithm makes it possible to reduce the total time of information exchange in the network of autonomous underwater vehicles and, as a result, increase the energy efficiency of the network. The paper describes the procedure for constructing a dynamic routing table in the network, an algorithm for scheduling exchanges. The results of modelling the operation of the scheduling algorithm are presented.

关键词： Autonomous underwater vehicles scheduling algorithms Heuristic algorithms Optimal scheduling Routing Dynamic scheduling Repeaters

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Storage-Aware scheduling Algorithm for Reservoir Switching Minimization on Digital Microfluidic Biochips

Storage-Aware Scheduling Algorithm for Reservoir Switching M...

引用

International Symposium on VLSI Design, Automation and Test (VLSI-DAT)

作者： Song, Ling-Yen Yeh, Chih-Shen Liu, Chien-Nan Huang, Juinn-Dar Natl Chiao Tung Univ Inst Elect Hsinchu Taiwan

ISBN: (纸本)9781665419154

Design automation of Digital Microfluidic biochip (DMFB) is one of the active research topics in recent years. A couple of studies have been conducted to minimize the reservoir switching count, which significantly speeds up a multi-reactant mixing process. In general, it is easier to reduce the switching count if more on-chip storage units are available. Nevertheless, in reality, the number of storages is often limited due to the chip fabrication cost. Therefore, in this paper, we present a storage-aware scheduling algorithm for reservoir switching minimization. Experimental results demonstrate that the proposed algorithm can reduce the storage requirement by 44% while still achieving a 38% decrease in the reservoir switching count when compared with a state-of-the-art method.

关键词： scheduling algorithms

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READYS: A Reinforcement Learning Based Strategy for Heterogeneous Dynamic scheduling

READYS: A Reinforcement Learning Based Strategy for Heteroge...

引用

IEEE International Conference on Cluster Computing (Cluster)

作者： Grinsztajn, Nathan Beaumont, Olivier Jeannot, Emmanuel Preux, Philippe Univ Lille INRIA CNRS UMR CRIStAL 9189 Lille France Univ Bordeaux Inria Bordeaux Sud Ouest Bordeaux France

ISBN: (纸本)9781728196664

In this paper, we propose READYS, a reinforcement learning algorithm for the dynamic scheduling of computations modeled as a Directed Acyclic Graph (DAGs). Our goal is to develop a scheduling algorithm in which allocation and scheduling decisions are made at runtime, based on the state of the system, as performed in runtime systems such as StarPU or ParSEC. Reinforcement Learning is a natural candidate to achieve this task, since its general principle is to build step by step a strategy that, given the state of the system (the state of the resources and a view of the ready tasks and their successors in our case), makes a decision to optimize a global criterion. Moreover, the use of Reinforcement Learning is natural in a context where the duration of tasks (and communications) is stochastic. We propose READYS that combines Graph Convolutional Networks (GCN) with an Actor-Critic Algorithm (A2C): it builds an adaptive representation of the scheduling problem on the fly and learns a scheduling strategy, aiming at minimizing the makespan. A crucial point is that READYS builds a general scheduling strategy which is neither limited to only one specific application or task graph nor one particular problem size, and that can be used to schedule any DAG. We focus on different types of task graphs originating from linear algebra factorization kernels (CHOLESKY, LU, QR) and we consider heterogeneous platforms made of a few CPUs and GPUs. We first propose to analyze the performance of READYS when learning is performed on a given (platform, kernel, problem size) combination. Using simulations, we show that the scheduling agent obtains performances very similar or even superior to algorithms from the literature, and that it is especially powerful when the scheduling environment contains a lot of uncertainty. We additionally demonstrate that our agent exhibits very promising generalization capabilities. To the best of our knowledge, this is the first paper which shows that reinforc

关键词： Schedules Runtime Uncertainty scheduling algorithms Stochastic processes Reinforcement learning Dynamic scheduling

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scheduling Containers Rather Than Functions for Function-as-a-Service 21

Scheduling Containers Rather Than Functions for Function-as-...

引用

21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid)

作者： Kim, Dong Kyoung Roh, Hyun-Gul NAVER Corp Seongnam Si Gyeonggi Do South Korea NAVER Cloud Corp Seongnam Si Gyeonggi Do South Korea

ISBN: (纸本)9781728195865

Function-as-a-Service (FaaS) is a compelling technology that allows users to run functions in an event-driven way without concerns about server management. Container-based virtualization enables functions to run in a lightweight and isolated run-time environment, but frequent function executions accompanied with container initialization (cold starts) make the platform busy and unresponsive. For performance sake, warm starts, which is to execute functions on already initialized containers, are encouraged, and thus FaaS platforms make efforts to schedule functions to warm containers. From our experience operating an on-premise FaaS platform, we found that the existing scheduler showed poor performance and unstable behavior against multi-tenant and highly concurrent workloads. This paper proposes a novel FaaS scheduling algorithm, named FPCSch, that schedules Function-Pulling-Containers instead of scheduling functions to containers. As FPCSch lets containers continuously pull functions of the same type, cold starts decrease dramatically. Our evaluations show that Apache OpenWhisk equipped with FPCSch has many desirable features for FaaS platforms;(1) quite stable throughput against the multi-tenant workloads mixed by the increasing numbers of function types, (2) growing throughput for increasing concurrency, (3) uniformly load-balancing resource-intensive workloads, and (4) nearly proportional performance for scale-out.

关键词： Concurrent computing Schedules Cloud computing scheduling algorithms FAA Containers Throughput

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Decentralized Low-Latency Task scheduling for Ad-Hoc Computing 35

Decentralized Low-Latency Task Scheduling for Ad-Hoc Computi...

引用

35th IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： Edinger, Janick Breitbach, Martin Gabrisch, Niklas Schafer, Dominik Becker, Christian Rizk, Amr Univ Hamburg Hamburg Germany Univ Mannheim Mannheim Germany Univ Duisburg Essen Duisburg Germany

ISBN: (纸本)9781665440660

End users can mutually share their computing resources in ad-hoc computing environments with code offloading. This augments the computational power of resource-constrained mobile devices and enables interactive user-facing applications that would otherwise exceed single device capabilities. However, ad-hoc computing comes along with new challenges such as heterogeneity and unreliability of devices. Resource consumers have to make task scheduling decisions without relying on a centralized scheduler to facilitate sub-second response times in environments with communication latencies that are in the order of the task execution limes. In this paper, we present a decentralized low-latency task scheduling approach that minimizes job execution times in heterogeneous ad-hoc environments. We propose two decentralized task scheduling algorithms that select powerful computing resources for parallel task execution while avoiding delays that arise from congested devices. We provide an analytical model of the performance of these algorithms before conducting an extensive evaluation based on real-world applications and a realistic computing infrastructure. Our results show that decentralized scheduling can dynamically adapt to varying system load and outperform a central scheduler in both task and job execution times, which enables low-latency task offloading in ad-hoc environments.

关键词： Performance evaluation Schedules Processor scheduling scheduling algorithms Heuristic algorithms Probability Mobile handsets

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Analysis of Practical Frequency Selective scheduling algorithms in LTE Networks

Analysis of Practical Frequency Selective Scheduling Algorit...

引用

IEEE Vehicular Technology Conference

作者： Faris Alfarhan Regis Lerbour Yann Le Helloco Gregory Donnard InfoVista Gatineau Canada and Les Ulis

ISBN: (纸本)9781479944484

The use of orthogonal frequency division multiple access (OFDMA) in Long Term Evolution (LTE) and LTE-Advanced systems facilitates the potential for scheduling cell users on orthogonal time-frequency resource blocks selectively. This paper identifies several frequency selective scheduling (FSS) algorithms and studies their performance and optimality under certain identified constraints in practice. The performance is studied under the limiting factors of cell load, user mobility, the number of users per cell, data traffic characteristics, and the LTE standards constraint of using a single modulation and coding scheme (MCS) across assigned resource blocks. To address the single MCS restriction, a dynamic Proportional Fair (PF) scheduling algorithm is developed to achieve optimal allocation under this constraint. The gain either in signal-to-interference-plus-noise ratio (SINR) or cell throughput achieved from these algorithms is statistically quantified using detailed LTE system level simulations.

关键词： LTE LTE-Advanced Cellular Systems OFDMA Frequency-Selective scheduling algorithms Proportional Fair

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FlowToss: Fast Wait-Free scheduling of Deterministic Flows in Time Synchronized Networks 20

FlowToss: Fast Wait-Free Scheduling of Deterministic Flows i...

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IFIP Networking Conference and Workshops (IFIP Networking)

作者： Bhatia, Randeep Lakshman, T. V. Ozkoc, Mustafa F. Panwar, Shivendra Nokia Bell Labs Holmdel NJ USA New York Univ Dept Elect & Comp Engn New York NY 10012 USA

ISBN: (纸本)9783903176393

Motivated by important industrial automation use cases, such as closed loop motion control and autonomous mobile robots, we study wait-free scheduling of periodic flows with stringent delay and jitter requirements in time sensitive networks. The goal is to assign initial transmission time-slots to periodic flows so that network queuing delays are eliminated or are very small. We make use of B ' ezout's Identity to develop simple and fast scheduling algorithms for this NP-hard problem. Operating in an online mode, our algorithms can quickly allocate contention free start time-slots to new flows, without changing allocations of already scheduled flows. Our main results are greedy and random scheduling algorithms that can trade speed for solution quality. Our simulations on different network topologies show that these algorithms are computationally efficient and can easily schedule a large number of flows, thus meeting the requirements of many industrial automation use cases.

关键词： Time Sensitive Networking Zero Queuing scheduling algorithms Industrial Automation

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